similar to: How to load a big txt file

Dear List, I have another question to bother you about how to do clustering. My data consists of 49 columns (49 variables) and 238804 rows. I would like to do hierarchical clustering (unsupervised clustering and PCA). So far I tried pvclust (www.is.titech.ac.jp/~shimo/prog/*pvclust* /) but I always had the problem like for R like "cannot allocate the memory". I am curious about what

Hello, I didn't give enough information when I sent an query before, so I'm trying again with a more detailed explanation: In this data set, each patient has a different number of measured variables (they represent tumors, so some people had 2 tumors, some had 5, etc). The problem I have is that often in later cycles for a patient, tumors that were originally measured are now missing (or

Hi, I am trying to plot the following data so that it can be visually represented well. I tried the dotchart but I felt it was too spread out. Then I tried the barplot which is good enough for me. Is there a way to give the labels for the y-axis as in the dot chart? Also, I feel the grey level is confusing, so is there options for designs within the bars? I cannot use color as the journal wants

Dear all, please could you advise me on the following : I've written a R script that reads 3 arguments from the command line, i.e. : " args <- commandArgs(TRUE) TUMOR <- args[1] GERMLINE <- args[2] CHR <- args[3] ". when I submit the R script to a PBS HPC scheduler, I do the following (below), but ... I am getting an error message. (I am not posting the error message,

Hi all, I got one problem with comparing strings like if any string is like "*RIGHT, EPICARDIUM: FOCUS, GRAY-WHITE, SINGLE, APPROX 0.6 CM IN DIAMETER*." and i have to compare "*GRAY-WHITE*" with the above string or otherwise i have to compare " *TUMOR BENIGN*" this string with "*MEDULLRY TUMOR BENIGN,TYP PHEOCHROMOCYTOMA*" i

This sounds like an operating system specific question, in that "submit the R script to a PBS HPC scheduler" would be the kind of action that would run R with very different environment variables and possibly different access credentials than your usual interactive terminal. A thorough reading of the "Installation and Administration Guide" and some study of your HPC

Hi, The problem is most likely, you need to call a R CMD BATCH with your arguments and the R-script inside of a shell script that you submit to your qsub. Unfortunately we don't use qsub anymore so can't test it, but it should be as follows: R-script eg. test.R: > ##First read in the arguments listed at the command line > args=(commandArgs(TRUE)) > > ##args is now a list of

Hi, I am having troubles with creating an eSet and would appreciate any help on the following problem. I am trying to create an eSet using the following code pd <- read.table(file="pdata.txt",header =TRUE,row.names=1); colnames(pd) <- c("type","tumor","time","id"); pdN <- list(type =

Hello, Would you tell my how to extract a result from a test - it's justified because I need to run this test many times. Here is an example from authors' test: > library("coin") > lungtumor <- data.frame(dose = rep(c(0, 1, 2), c(40, 50, 48)), tumor = c(rep(c(0, 1), c(38, 2)), rep(c(0, 1), c(43, 7)), rep(c(0, 1), c(33, 15)))) > ca.test<-independence_test(tumor ~

Hello, I am trying to explore a classification with GGobi. I am trying to generate additional data according to the model so I can draw the decision boundaries on the GGobi plot. The problem is that I always get the same error: Error in predict.lda(model,data): wrong number of variables, even if I know that I used the same number of variables for the model generation (6) and for the additional

I am interested in plotting histograms for the following data Isoform Tumor_65_198 Tumor_50_192 Tumor_80_167 Tumor_80_204 Tumor_95_197 Tumor_70_189 Tumor_90_202 Tumor_40_177 Tumor_60_21 Tumor_70_174 Tumor_70_147 Tumor_50_5 ABCC4-2007 1 1 1 6 1 9 10 1 2 0 10 1 ABCC4-2008 5 8 7 5 3 10 5 5 7 3 10 3 ABCC4-2009 0 0 0 0 0 0 0 0 0 0 0 0 ABCC4-2010

Dear sir, I am Shibu John from Thrombosis Research Institute India. It is a multidisciplinary organisation concerned with the interrelated problems of thrombosis and atherosclerosis. I was searching for Cochran armitage trend test program in R. Then I had seen your R coding for C-A trend test. I tried that in the R software. But I can?t run the program due the [Error: could not find function

In the vcdExtra package on R-Forge, I have functions and generic methods for calculating log odds ratios for R x C x strata tables. I'd like to define methods for fitting weighted lm()s to the resulting loddsratio objects, but I'm having problems figuring out how to do this generally. # install.packages("vcdExtra", repos="http://R-Forge.R-Project.org")

Hello, I would like, if it is possible, to compare the effect of a variable across regression models. I have looked around but I haven't found anything. Maybe someone could help? Here is the problem: I am studying the effect of a variable (age) on an outcome (local recurrence: lr). I have built 3 models: - model 1: lr ~ age y = \beta_(a1).age - model 2: lr ~ age + presentation

May I ask a clinical question? For a trial, we have a treatment group of small size, say 30 patients. We want to selectmatching control patients from a bigger group (100 patients) in terms of several clinical variables, such as age, tumor stage etc. This practice is to select the closest matching set of control cases. I wonder if R has any routine or package that can help with this problem.

Dear R-help, I am having a problem with the interpretation of result from validate.cph in the Design package. My purpose is to fit a cox model and validate the Somer's Dxy. I used the hypothetical data given in the help manual with modification to the cox model fit. My research problem is very similar to this example. This is the model without stratification: > library(Design) > f1

Dear R people Could you please help with following Trying to compare accuracy of tumor size evaluation by different methods. So data looks like id true metod1 method2 ... 1 2 2 2.5 2 1.5 2 2 3 2 2 2 etc. Could you please give a hint how to deal with that. Seems like {merror} does not suite to me because I am trying to compare accuracy of measurements with their true known values not just

Hello, I would like to plot the results of a LDA analysis plotting the discriminant scores with the decission boundaries on it with rggobi. I have GGobi already installed on my computer. I have three classes, so the plot would be LD1xLD2 plus the decission boundaries. Here there is the code I use make the plot: library(MASS) data <- zgcppr273K.pca$x[,1:7] Tumor <-

Hello everyone, I have two problems which I am unable to solve : 1.I am trying to add the  row labels (g1-g2000) to the very left of a data table. The data table is 2000 rows  by 62 columns.I have used the following code. read.table(file="C:\\Documents and Settings\\Owner\\My Documents\\colon cancer1.txt",header=T,row.names=1) rowname(dat) <- paste("g", c(1:nrow(dat)),

Dear R-help members, Apologies - I am posting on behalf of a colleague, who is a little puzzled as STATA and R seem to be yielding different survival estimates for the same dataset when treating a variable as ordinal. Ordered() is used to represent an ordinal variable) I understand that R's coxph (by default) uses the Efron approximation, whereas STATA uses (by default) the Breslow. but we